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Footnote

Rez. in: ABI-Technik 21(2002) H.3, S.292 (E. Pietzsch): "Otto C. Oberhauser hat mit seiner Diplomarbeit eine beeindruckende Analyse digitalisierter Zettelkataloge (CIPACs) vorgelegt. Die Arbeit wartet mit einer Fülle von Daten und Statistiken auf, wie sie bislang nicht vorgelegen haben. BibliothekarInnen, die sich mit der Digitalisierung von Katalogen tragen, finden darin eine einzigartige Vorlage zur Entscheidungsfindung. Nach einem einführenden Kapitel bringt Oberhauser zunächst einen Überblick über eine Auswahl weltweit verfügbarer CIPACs, deren Indexierungsmethode (Binäre Suche, partielle Indexierung, Suche in OCR-Daten) und stellt vergleichende Betrachtungen über geographische Verteilung, Größe, Software, Navigation und andere Eigenschaften an. Anschließend beschreibt und analysiert er Implementierungsprobleme, beginnend bei Gründen, die zur Digitalisierung führen können: Kosten, Umsetzungsdauer, Zugriffsverbesserung, Stellplatzersparnis. Er fährt fort mit technischen Aspekten wie Scannen und Qualitätskontrolle, Image Standards, OCR, manueller Nacharbeit, Servertechnologie. Dabei geht er auch auf die eher hinderlichen Eigenschaften älterer Kataloge ein sowie auf die Präsentation im Web und die Anbindung an vorhandene Opacs. Einem wichtigen Aspekt, nämlich der Beurteilung durch die wichtigste Zielgruppe, die BibliotheksbenutzerInnen, hat Oberhauser eine eigene Feldforschung gewidmet, deren Ergebnisse er im letzten Kapitel eingehend analysiert. Anhänge über die Art der Datenerhebung und Einzelbeschreibung vieler Kataloge runden die Arbeit ab. Insgesamt kann ich die Arbeit nur als die eindrucksvollste Sammlung von Daten, Statistiken und Analysen zum Thema CIPACs bezeichnen, die mir bislang begegnet ist. Auf einen schön herausgearbeiteten Einzelaspekt, nämlich die weitgehende Zersplitterung bei den eingesetzten Softwaresystemen, will ich besonders eingehen: Derzeit können wir grob zwischen Komplettlösungen (eine beauftragte Firma führt als Generalunternehmung sämtliche Aufgaben von der Digitalisierung bis zur Ablieferung der fertigen Anwendung aus) und geteilten Lösungen (die Digitalisierung wird getrennt von der Indexierung und der Softwareerstellung vergeben bzw. im eigenen Hause vorgenommen) unterscheiden. Letztere setzen ein Projektmanagement im Hause voraus. Gerade die Softwareerstellung im eigenen Haus aber kann zu Lösungen führen, die kommerziellen Angeboten keineswegs nachstehen. Schade ist nur, daß die vielfältigen Eigenentwicklungen bislang noch nicht zu Initiativen geführt haben, die, ähnlich wie bei Public Domain Software, eine "optimale", kostengünstige und weithin akzeptierte Softwarelösung zum Ziel haben. Einige kritische Anmerkungen sollen dennoch nicht unerwähnt bleiben. Beispielsweise fehlt eine Differenzierung zwischen "Reiterkarten"-Systemen, d.h. solchen mit Indexierung jeder 20. oder 50. Karte, und Systemen mit vollständiger Indexierung sämtlicher Kartenköpfe, führt doch diese weitreichende Designentscheidung zu erheblichen Kostenverschiebungen zwischen Katalogerstellung und späterer Benutzung. Auch bei den statistischen Auswertungen der Feldforschung hätte ich mir eine feinere Differenzierung nach Typ des CIPAC oder nach Bibliothek gewünscht. So haben beispielsweise mehr als die Hälfte der befragten BenutzerInnen angegeben, die Bedienung des CIPAC sei zunächst schwer verständlich oder seine Benutzung sei zeitaufwendig gewesen. Offen beibt jedoch, ob es Unterschiede zwischen den verschiedenen Realisierungstypen gibt.
Nun haben Diplomarbeiten einen eigenen Charakter. Ihre Zielsetzung ist nicht unbedingt, Handlungsleitfäden zu geben. Manche FachkollegInnen, die schon selbst mit der Digitalisierung von Katalogen zu tun hatten, fragen sich aber, ob die jeweils gefundene Lösung denn tatsächlich die "beste" erreichbare war, ob es sich lohnt, über Verbesserungen nachzudenken, wie ihre Lösung im Vergleich zu anderen steht, ob die eingesetzte Recherchesoftware gute Ergebnisse liefert, ob die zunächst vielleicht niedrigen Erstellungskosten nicht doch relativ lange Verweildauern, d.h. verdeckte Kosten, bei der Recherche zur Folge haben. Oberhauser gibt dazu lediglich am Rande einige Hinweise. Wünschenswert wäre, wenn derartige Detailuntersuchungen in weiteren Arbeiten vorgenommen würden."

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Abstract

While being theoretically so widely available, information can be restricted from a more general use by linguistic barriers. The linguistic aspects of the information languages and particularly the chances of an enhanced access to information by means of multilingual access facilities will make the substance of this thesis. The main problem of this research is thus to demonstrate that information retrieval can be improved by using multilingual thesaurus terms based on an intermediate or switching language to search with. Universal classification systems in general can play the role of switching languages for reasons dealt with in the forthcoming pages. The Universal Decimal Classification (UDC) in particular is the classification system used as example of a switching language for our objectives. The question may arise: why a universal classification system and not another thesaurus? Because the UDC like most of the classification systems uses symbols. Therefore, it is language independent and the problems of compatibility between such a thesaurus and different other thesauri in different languages are avoided. Another question may still arise? Why not then, assign running numbers to the descriptors in a thesaurus and make a switching language out of the resulting enumerative system? Because of some other characteristics of the UDC: hierarchical structure and terminological richness, consistency and control. One big problem to find an answer to is: can a thesaurus be made having as a basis a classification system in any and all its parts? To what extent this question can be given an affirmative answer? This depends much on the attributes of the universal classification system which can be favourably used to this purpose. Examples of different situations will be given and discussed upon beginning with those classes of UDC which are best fitted for building a thesaurus structure out of them (classes which are both hierarchical and faceted)...

Content

Inhalt: INFORMATION LANGUAGES: A LINGUISTIC APPROACH MULTILINGUAL ASPECTS IN INFORMATION STORAGE AND RETRIEVAL COMPATIBILITY AND CONVERTIBILITY OF INFORMATION LANGUAGES CURRENT TRENDS IN MULTILINGUAL ACCESS BUILDING UDC-BASED MULTILINGUAL THESAURI ONLINE APPLICATIONS OF THE UDC-BASED MULTILINGUAL THESAURI THE IMPACT OF SPECIFICITY ON THE RETRIEVAL POWER OF A UDC-BASED MULTILINGUAL THESAURUS FINAL REMARKS AND GENERAL CONCLUSIONS Proefschrift voorgelegd tot het behalen van de graad van doctor in de Taal- en Letterkunde aan de Universiteit Antwerpen. - Vgl.: http://dlist.sir.arizona.edu/1862/.

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Content

Diese Publikation entstand im Rahmen einer Bachelor Thesis zum Abschluss Bachelor of Science (BSc) FHO in Informationswissenschaft. Vgl. unter: http://www.fh-htwchur.ch/uploads/media/CSI_44_Baier.pdf.

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Abstract

In this thesis, we present an ontology-based information extraction and retrieval system and its application to soccer domain. In general, we deal with three issues in semantic search, namely, usability, scalability and retrieval performance. We propose a keyword-based semantic retrieval approach. The performance of the system is improved considerably using domain-specific information extraction, inference and rules. Scalability is achieved by adapting a semantic indexing approach. The system is implemented using the state-of-the-art technologies in SemanticWeb and its performance is evaluated against traditional systems as well as the query expansion methods. Furthermore, a detailed evaluation is provided to observe the performance gain due to domain-specific information extraction and inference. Finally, we show how we use semantic indexing to solve simple structural ambiguities.

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Abstract

In this thesis, we will present methods for introducing ontologies in information retrieval. The main hypothesis is that the inclusion of conceptual knowledge such as ontologies in the information retrieval process can contribute to the solution of major problems currently found in information retrieval. This utilization of ontologies has a number of challenges. Our focus is on the use of similarity measures derived from the knowledge about relations between concepts in ontologies, the recognition of semantic information in texts and the mapping of this knowledge into the ontologies in use, as well as how to fuse together the ideas of ontological similarity and ontological indexing into a realistic information retrieval scenario. To achieve the recognition of semantic knowledge in a text, shallow natural language processing is used during indexing that reveals knowledge to the level of noun phrases. Furthermore, we briefly cover the identification of semantic relations inside and between noun phrases, as well as discuss which kind of problems are caused by an increase in compoundness with respect to the structure of concepts in the evaluation of queries. Measuring similarity between concepts based on distances in the structure of the ontology is discussed. In addition, a shared nodes measure is introduced and, based on a set of intuitive similarity properties, compared to a number of different measures. In this comparison the shared nodes measure appears to be superior, though more computationally complex. Some of the major problems of shared nodes which relate to the way relations differ with respect to the degree they bring the concepts they connect closer are discussed. A generalized measure called weighted shared nodes is introduced to deal with these problems. Finally, the utilization of concept similarity in query evaluation is discussed. A semantic expansion approach that incorporates concept similarity is introduced and a generalized fuzzy set retrieval model that applies expansion during query evaluation is presented. While not commonly used in present information retrieval systems, it appears that the fuzzy set model comprises the flexibility needed when generalizing to an ontology-based retrieval model and, with the introduction of a hierarchical fuzzy aggregation principle, compound concepts can be handled in a straightforward and natural manner.

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Content

Vgl.: http://hdl.handle.net/10023/3462. - Steht nicht im Volltext zur Verfügung.

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Abstract

Multiword expressions (MWEs) are lexical items that can be decomposed into single words and display lexical, syntactic, semantic, pragmatic and/or statistical idiosyncrasy (Sag et al., 2002; Kim, 2008; Calzolari et al., 2002). The proper treatment of multiword expressions such as rock 'n' roll and make a decision is essential for many natural language processing (NLP) applications like information extraction and retrieval, terminology extraction and machine translation, and it is important to identify multiword expressions in context. For example, in machine translation we must know that MWEs form one semantic unit, hence their parts should not be translated separately. For this, multiword expressions should be identified first in the text to be translated. The chief aim of this thesis is to develop machine learning-based approaches for the automatic detection of different types of multiword expressions in English and Hungarian natural language texts. In our investigations, we pay attention to the characteristics of different types of multiword expressions such as nominal compounds, multiword named entities and light verb constructions, and we apply novel methods to identify MWEs in raw texts. In the thesis it will be demonstrated that nominal compounds and multiword amed entities may require a similar approach for their automatic detection as they behave in the same way from a linguistic point of view. Furthermore, it will be shown that the automatic detection of light verb constructions can be carried out using two effective machine learning-based approaches.

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Abstract

This PhD-thesis describes how to effectively explore linked data on the Web. The main focus is on scenarios where users want to discover relationships between resources rather than finding out more about something specific. Searching for a specific document or piece of information fits in the theoretical framework of information retrieval and is associated with exploratory search. Exploratory search goes beyond 'looking up something' when users are seeking more detailed understanding, further investigation or navigation of the initial search results. The ideas behind exploratory search and querying linked data merge when it comes to the way knowledge is represented and indexed by machines - how data is structured and stored for optimal searchability. Queries and information should be aligned to facilitate that searches also reveal connections between results. This implies that they take into account the same semantic entities, relevant at that moment. To realize this, we research three techniques that are evaluated one by one in an experimental set-up to assess how well they succeed in their goals. In the end, the techniques are applied to a practical use case that focuses on forming a bridge between the Web and the use of digital libraries in scientific research. Our first technique focuses on the interactive visualization of search results. Linked data resources can be brought in relation with each other at will. This leads to complex and diverse graphs structures. Our technique facilitates navigation and supports a workflow starting from a broad overview on the data and allows narrowing down until the desired level of detail to then broaden again. To validate the flow, two visualizations where implemented and presented to test-users. The users judged the usability of the visualizations, how the visualizations fit in the workflow and to which degree their features seemed useful for the exploration of linked data.